Model Name and Version: ObjECTS GCAM.
Using the Model: GCAM is now freely available as a community model. See GCAM Community
Model Documentation: GCAM is documented in a wiki. This wiki includes detailed information about the assumptions and data sources used to develop the model. See GCAM Wiki.
Model Type: Dynamic-recursive model (economy, energy and land-use) including numerous energy supply technologies, agriculture and land-use model, and a reduced-form climate model. Sixteen emissions tracked including CO2, CH4, N2O, and SO2. 5-year time step. Run period 1990 – 2095.
Developer/Home Institution: Joint Global Change Research Institute (PNNL). Contacts: Pralit Patel (pralit.patel@pnnl.gov) or Leon Clarke (leon.clarke@pnnl.gov).
Energy Sector Detail: Three end-use sectors (Buildings, Industry, Transportation). Energy supply and transformation sectors: fossil-fuels (oil, natural gas, coal), biomass (traditional & modern), electricity, hydrogen, synthetic fuels.
Regional Detail: Global coverage with 14 regions (United States, Canada, Western Europe, Japan, Australia & New Zealand, Former Soviet Union, Eastern Europe, Latin America, Africa, Middle East, China [& Asian Reforming Economies], India, South Korea, Rest of South & East Asia)
Key Drivers: Regional population and labor productivity growth assumptions drive the energy and land-use systems.
Technology Detail: GCAM includes numerous technology options to produce, transform, and provide energy services as well as to produce agriculture and forest products, and to determine land use and land cover.
Primary energy detail: Oil (conventional and unconventional), Natural Gas, Coal, Bioenergy, Hydroelectric power, Wind, Solar (various technologies), and geothermal. Bioenergy production includes: Traditional, Crop residue, and Dedicated bioenergy crops (Bioenergy crops generated regionally by the GCAM agriculture-land-use-terrestrial-carbon-cycle model).
Energy Transformation Technologies Include: Electricity generation, Hydrogen production, and Synfuels.
- Petroleum refining (conventional and unconventional primary liquids to fuels for end-use sectors)
- Electric generation (various power generation technologies using the following fuel inputs: Coal, Oil, Gas, Biomass, Hydro, Nuclear, Wind, Solar PV; includes CO2 capture and storage technology options for hydrocarbon fuel inputs)
- Hydrogen production using various feedstocks (Coal, Oil, Gas, Biomass, water using Electrolysis, and thermal dissociation)
- Synthetic fuels production (liquids and gases from coal, oil, gas, biomass), geologic carbon storage from hydrocarbon fuels (fossil fuels and bioenergy) (electric generation, hydrogen generation, synthetic fuel production).
Energy Demand: Technology-based U.S. end-use sectors.
- Transportation by mode (Passenger: light duty vehicles, bus, train, air, motorcycle; Freight: truck, ship, rail, air) and technology (e.g., ICE cars, ICE light trucks, hybrid cars, electric cars, fuel-cell cars).
- Separate commercial and residential buildings by service (heating, cooling, lighting, hot water, other) and technology (e.g., gas or oil furnace, electric baseboard, electric heat pump).
- Industrial energy use by sector (9 manufacturing sectors; 4 non-manufacturing) and end-use (boilers, process heat, machine drive, HVAC, electro-chemical, feedstocks, other).
Agriculture-Land-Use Model: The agriculture-land-use model (AgLU) endogenously determines land use, land cover, and the stocks and flows of carbon from terrestrial reservoirs. AgLU is fully integrated with the GCAM energy and economy modules. In GCAM 3.0, the model data for the agriculture and land use parts of the model is comprised of 151 subregions in terms of land use, based on a division of the extant agro-ecological zones (AEZs) within each of GCAM’s 14 global geo-political regions. Within each of these 151 subregions, land is categorized into approximately a dozen types based on cover and use. Some of these types, such as tundra and desert, are not considered arable. Among arable land types, further divisions are made for lands historically in non-commercial uses such as forests and grasslands as well as commercial forestlands and croplands. Production of approximately twenty crops is currently modeled, with yields of each specific to each of the 151 subregions. The model is designed to allow specification of different options for future crop management for each crop in each subregion. Stocks and flows of terrestrial carbon and other greenhouse gases are determined by associated land use and land cover and land-use-land-cover changes.
ObjECTS Framework: The GCAM is implemented within the Object-Oriented Energy, Climate, and Technology Systems (ObjECTS) framework. ObjECTS is a flexible, modular, Integrated Assessment modeling framework. The component-based structure of this model represents global energy, land-use, and economic systems through a component hierarchy that aggregates detailed technology information up to a global macroeconomic level. Input is provided by the flexible XML standard, where data is structured in an object hierarchy that parallels the model structure.
Special Features: Ability to understand the impact of technologies and policies related to GHG emissions in a national and global context. Ability to quickly evaluate technologies including carbon capture and storage. An embedded reduced form model of the carbon cycle, atmospheric chemistry and climate change, MAGICC, provides GHG concentrations, radiative forcing, and climate change. Flexible object-oriented structure allows new technologies and sectors to be quickly implemented.
References:
Edmonds, J., and J. Reilly (1985)Global Energy: Assessing the Future (Oxford University Press, New York) pp.317.
Edmonds, J., M. Wise, H. Pitcher, R. Richels, T. Wigley, and C. MacCracken. (1997) “An Integrated Assessment of Climate Change and the Accelerated Introduction of Advanced Energy Technologies”, Mitigation and Adaptation Strategies for Global Change, 1, pp. 311-39
Kim, S.H., J. Edmonds, J. Lurz, S. J. Smith, and M. Wise (2006) “The ObjECTS Framework for Integrated Assessment: Hybrid Modeling of Transportation ” Energy Journal (Special Issue #2) pp 51-80.
